Collect community CPU/GPU benchmark results

[initial-d]

Benchmark results from different machines will make the tensor factor engine easier to evaluate and compare.

Suggested steps:

1. Install the project with pip install -e .[dev].
2. Run make benchmark or a larger command from docs/benchmarking.md.
3. Open a benchmark issue with the printed Markdown table.
4. Include Python, PyTorch, CPU, GPU, CUDA availability, and commit SHA.

Good first contribution: submit one clean benchmark report from your machine.

[initial-d]

A first maintainer CPU baseline is now on the benchmark board:

https://github.com/initial-d/ml-quant-trading/blob/main/docs/benchmark_board.md

Next useful reports: CUDA GPU, Apple Silicon MPS if supported in future benchmark variants, Linux CPU, and larger panels.